Current and Past Research Projects

Grid Challenges for a Smart Transit System

 

 

Electric Vehicles lead to the electrification of transport that is drawing increasing attention from governments all across the world. Recognizing the depleting oil resources, dependence on foreign oil and increasing greenhouse gas emissions the transition to electrification is inevitable and most promising path to secure energy future. This electrification leads to linking both transportation and electricity sectors defining new domain of problems and needs that have not been looked at before and are daunting. Transit industry believes that electric vehicles will increase public transportation ridership and this research proposes a sustainable on-demand transit system which creates integration challenges with the grid.

With private transportation, electric vehicles charging stations are distributed over grid however with smart transit system the vehicle charging stations will be concentrated to a limited number of feeders in the grid, as a result of fixed pathways, which would have significant impact on the grid. Under the smart grid paradigm the smart charging of EVs can be utilized which would prevent overloading of devices and thus instability of the grid. This overloading problem is further aggravated if routing needs require electric vehicles to be charged and be ready for peak demands of transportation. On a very hot summer day, when electric demand is at its peak electric vehicles can serve as storage devices, providing power back to grid but transportation needs may take precedence. This inter-dependence of transportation and power needs require developing intelligent solutions to make the most efficient use of electric vehicles.

Can the interactions of transit system with grid be modeled? What types of models are needed? How can the resources be utilized optimally under changing system conditions and needs? For example how to achieve a least cost operation at some instants whereas maximized charging of vehicles, electric losses minimization and balancing system at other instants.

Electric vehicles recharge from power grid and hence, they will have a significant impact on grid’s operation. To make electric vehicles more sustainable the energy for charging can come from renewable sources and the power for recharging of vehicles may be much less than the renewable energy produced, but it poses challenges to the grid operation because of intermittencies in renewable sources and time period of charging of vehicles.  Evaluating the dynamic performance of wind and solar system with electric vehicles in a grid interface has been of much interest to the utilities recently. Maintaining the grid stability during both, proposed transit system utilizing grid power, and, proposed transit system delivering grid power along with satisfying the transportation needs is crucial to this research. Electric vehicles in the proposed transport can discharge during grid instability states, for frequency regulation and voltage dips requiring Multi-Agent coordinated control.

Key issues for the proposed transit system operation with distribution system are voltage regulation, flicker, var support, reactance-to-resistance ratio of system, load type, controllers, type of turbine in case of wind generators and type of charging for electric vehicles. Our motive is not only to realize the utilization of electric vehicle for rapid transit but also to improve upon the present system operation by bringing together demand response and electric vehicles in addressing the variability of wind and solar in the distribution system employing this transportation.

Collaborator(s):

• Sarika Khushalani Solanki, WVU (PI of project),
• Jignesh Solanki, WVU, (Co-PI)
  
• Qipeng Zhenge, UCF
  
• David Martinalli, WVU.
  

Sponsor(s):

• National Science Foundation: Program Director - Dr. Paul Werbose

Joint Research - Renewable Energy Integration on American Electric Power Distribution Network

 

 

Due to government mandate of using renewable energy sources (RESs) as part of the portfolio as clean energy resource, utilities are integrating these sources in to their existing electric transmission and distribution grid. These renewable energy sources are inherently intermittent and create lot of challenges for integrating in to the distribution system. This requires modeling and simulation of distribution system with RESs for planning and analysis. OpenDSS (also called DSS) is a comprehensive electrical power system tool for electric utility distribution systems developed by Electric Power Research Institute (EPRI) and it is an open source tool for simulating distribution systems and performs various analyses namely power flow, harmonics and dynamics in frequency domain. Time series distribution analysis is supported by OpenDSS which can be utilized to run annual load simulations along with daily/yearly power flow solution modes. The harmonic flow solution is a fundamental feature of OpenDSS and it provides a good platform for analyzing harmonic effects of wind turbines and inverter based PV on voltage regulators and capacitor switching. These capabilities of the tool have been used to model and analyze American Electric Power distribution system with solar/wind integration at different locations.

The short term objective of our research is to model AEP system in OpenDSS and analyze the different penetration levels of solar generation at different locations. The long term objective of the proposal is not restricted to steady state analysis of different penetration levels but to analyze the dynamic impacts of different locations and penetration levels of solar generation on distribution system. Ongoing research at WVU on fault ride through capability, voltage flickers and harmonic reduction using the solar generation will be leveraged for AEP system

Sponsor(s):

• American Electric Power: Tom Weaver

 Developing Demand Response Algorithms for the Clean Energy Smart Grid 

 

 

Department of Energy is committed to achieving a national, clean-energy Smart Grid, including both the transmission and distribution of electricity.  Building, operating, and maintaining a modern electricity system that integrates sources of renewable energy and addresses carbon and environmental concerns requires changes in our current electric power system.  
The advent of Smart Grids requires an increase in metering and communications, allowing for reliable collection and processing of customer side data; it also requires improved load management techniques for a secure and reliable electrical power system operation.   One integral part of the Smart Grid paradigm is Demand Response (DR), an integrated demand management system.  DR algorithms can intelligently control multiple distribution sources of electricity, and the generation and loads to meet the grid’s power delivery capabilities at any time.  DR algorithms provide relief to further investment in expansion of utility infrastructure, minimize blackouts, minimize losses and provide benefits to customers and utilities.  Furthermore, with an automated metering infrastructure through a fiber network and mesh radio systems that communicate with and collect data from automated meters, the ability to more specifically manage demand and energy usage becomes available.

In its ruling on October 17, 2009 Federal Energy Regulatory Commission (FERC) states “DR can provide competitive pressure to reduce wholesale power prices; increases awareness of energy usage; provides for more efficient operation of markets; mitigates market power; enhances reliability; and in combination with certain new technologies, can support the use of renewable energy resources, distributed generation, and advanced metering.”  To fulfill the Smart Grid initiatives, meeting load without increasing generation capacity or adding new lines, an economical and technically viable solution is needed.  Efficient DR algorithms that guarantee security, stability, and reliability are the necessary foundation for implementing Smart Grid initiatives. 

The long term goal is to establish a comprehensive demand response algorithms to provide state-of-the art innovations in Distribution Management Systems (DMS) for the modern electricity system. 

Sponsor(s):

• West Virginia University - PSCoR Program